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Hearing Aid Use, Satisfaction in Older Adults: Will Physician Visits Make a Difference?

2020· article· en· W3047317013 on OpenAlexaboutno aff
Desmond A. Nunez, Kevin Zhao

Bibliographic record

VenueThe Hearing Journal · 2020
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsHearing lossHearing aidAudiologyMedicinePsychological interventionPopulationHealth careIntervention (counseling)NursingEnvironmental health

Abstract

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The 2014-2016 National Health Interview Survey found that 15.9 percent of U.S. adults reported having hearing loss.1 Self-reports invariably underestimate the true prevalence of hearing loss possibly because of the insidious onset of the most prevalent type of acquired hearing loss: presbyacusis.2 This is confirmed by a recent national audiometric test-based study of a North American population that identified hearing loss prevalence rates as high as 65 percent in adults aged 70 to 79 years old.3iStock/sanjeri, audiology, primary care, hearing aids.Hearing aids are effective4 and common treatment options for hearing loss. However, hearing aid use is low, with only 3.7 percent of U.S. adults with hearing loss reporting owning a hearing aid.5 The reasons for this are uncertain, though subjects have reported being less satisfied with hearing aids than with similar sensory assistive devices such as eyeglasses.6In a literature review, Knudsen, et al.,7 concluded that perceived hearing disability was the only factor that affected both hearing aid use and satisfaction—an important finding illustrating adult hearing loss as a chronic condition that is amenable to management within the chronic care model advocated by Bodenheimer, et al.8 This model highlights that support for self-management and/or delivery system design-focused interventions can yield improved hearing health outcomes, thereby offering an alternative avenue for intervention to the more traditional audiological focus on hearing aid gain, amplification, and fit. The effects of self-management support and delivery system design on hearing aid use were studied in the Cochrane review by Baker, et al.9 Among the 32 studies reviewed, only two studies looked at the effect of self-support management on hearing aid use; however, these were not suitable for meta-analysis. Also, the researchers didn't find any statistically significant evidence that intervention combinations in the self-management and system design domains affected hearing aid use, though they found a reduction in hearing handicap.9 In a systematic review of the literature on hearing aid use and satisfaction, Mousavei, et al.,10searched a combination of keywords in the PubMed, Medline, and Embase databases and included studies published from January 1990 to January 2015 that focused on interventions aimed at improving hearing aid satisfaction and use and determinants of hearing aid use and satisfaction. Peer-reviewed articles that reported quantitative outcomes on a minimum of 20 older adult subjects were included in the review. Twenty-four studies were judged suitable for further study by two independent investigators. The subjects’ perceived severity of hearing loss and expectations of hearing aid benefit were positively correlated with hearing aid use. No specific factors conclusively affected hearing aid satisfaction. Hearing aid use and satisfaction were not affected by the patient's age or sex. No evidence showed that counseling, provided as a delivery system design intervention, improved hearing aid use or satisfaction. STUDY PREVIEW Based on existing literature, a multicenter randomized control trial was undertaken to investigate if a delivery system design intervention that includes a visit to a physician (family doctor or otolaryngologist/head and neck surgeon) during the hearing aid fitting process alter a patient's reported satisfaction with hearing aids.11 The trial was approved by the University of British Columbia's Clinical Research Ethics Board. Study participants were recruited from five audiology clinics in the Vancouver metropolitan area. Participants were adults 55 years of age or older who had hearing aid fitting for a sensorineural hearing loss greater than 25 dB, averaged over pure-tone audiometric measures of four frequencies in one or both ears. They were randomized to undergo standard-of-care hearing aid fitting alone or standard-of-care hearing aid fitting and a visit to their family doctor or an otolaryngologist/head and neck surgeon. At the visit, the physician conducted a Client Oriented Scale of Improvement (COSI)12 interview to see if the patient's hearing had changed following the hearing aid fitting. Participants completed the validated Satisfaction with Amplification in Daily Life (SADL) questionnaire13 three to four months after their initial fitting. At the time of interval analysis of the trial data, 94 patients had been recruited, with 57 and 37 randomized to the control and physician intervention groups, respectively. Eight patients in the control and three in the physician group didn't report for follow-up. SADL questionnaires were pending on nine control and 10 physician intervention patients. Therefore, data of 40 control and 24 physician intervention group patients were analyzed. The two groups were similar in age (72.8 and 70.3 years); sex (50% and 44% male); and PTA (43.1 and 49.2 dBHL). No statistically significant inter-group difference was found in the global SADL scores at three to four months follow-up (5.3 and 5.4; students’ t-test, p = 0.6). A chronic care system design intervention consisting of a single physician visit did not significantly change the level of satisfaction with hearing aids in a group of older adult hearing aid users. This finding is not definitive since a minimum of 40 patients is required in each arm of the study to show a standardized difference of 0.625 (0.5/0.8) at a five percent significance level, with a power of 80 percent based on the sample size nomogram by Altman.14 The physician group data set analyzed includes 24 patients and is thus short of the minimum sample size. The COVID-19 pandemic restrictions have delayed the final data accrual. However, it is anticipated that the shortfall will be filled as the data from patients who have been recruited after the interval analysis become available. The definitive results will then be reported.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.275
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
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